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non targeting negative control nc sirna  (Sangon Biotech)

 
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    Sangon Biotech non targeting negative control nc sirna
    Non Targeting Negative Control Nc Sirna, supplied by Sangon Biotech, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/non+targeting+negative+control+nc+sirna/control+negative+sirna/pm41752004-251-13-21
    Average 86 stars, based on 1 article reviews
    non targeting negative control nc sirna - by Bioz Stars, 2026-11
    86/100 stars

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    Related Articles

    Cell Culture:

    Article Title: A Functional Study of the Apoptosis Caspase Gene Family in the Sex Differentiation of Chinese Tongue Sole ( Cynoglossus semilaevis ).
    Article Snippet: .. Germ Cell Culture and siRNA Knockdown Specific siRNAs targeting caspase genes and a non-targeting negative control (NC) siRNA were synthesized by Sangon Biotech (Shanghai, China). ..

    Knockdown:

    Article Title: A Functional Study of the Apoptosis Caspase Gene Family in the Sex Differentiation of Chinese Tongue Sole ( Cynoglossus semilaevis ).
    Article Snippet: .. Germ Cell Culture and siRNA Knockdown Specific siRNAs targeting caspase genes and a non-targeting negative control (NC) siRNA were synthesized by Sangon Biotech (Shanghai, China). ..

    Negative Control:

    Article Title: A Functional Study of the Apoptosis Caspase Gene Family in the Sex Differentiation of Chinese Tongue Sole ( Cynoglossus semilaevis ).
    Article Snippet: .. Germ Cell Culture and siRNA Knockdown Specific siRNAs targeting caspase genes and a non-targeting negative control (NC) siRNA were synthesized by Sangon Biotech (Shanghai, China). ..

    Synthesized:

    Article Title: A Functional Study of the Apoptosis Caspase Gene Family in the Sex Differentiation of Chinese Tongue Sole ( Cynoglossus semilaevis ).
    Article Snippet: .. Germ Cell Culture and siRNA Knockdown Specific siRNAs targeting caspase genes and a non-targeting negative control (NC) siRNA were synthesized by Sangon Biotech (Shanghai, China). ..



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    Image Search Results


    ME1 expression analysis in pan-cancer. (A) Differences in ME1 expression between 33 normal and tumor tissues in TCGA from the TIMER2.0 database. (B) Differences in ME1 expression between cancers from the TCGA database and normal samples from the GTEx database. (C, D) ME1 expression level in GENT2 GPL96 and GPL570 . (E) Expression and distribution of ME1 in various organs. The left panel depicts the expression of ME1 in the corresponding tumor tissues, while the right panel represents the expression of ME1 in normal tissues. A darker color indicates a higher expression level of ME1.* p < 0.05, ** p < 0.01, *** p < 0.001.

    Journal: Frontiers in Immunology

    Article Title: The potential of ME1 in guiding immunotherapeutic strategies for ovarian cancer: insights from pan-cancer research

    doi: 10.3389/fimmu.2025.1571842

    Figure Lengend Snippet: ME1 expression analysis in pan-cancer. (A) Differences in ME1 expression between 33 normal and tumor tissues in TCGA from the TIMER2.0 database. (B) Differences in ME1 expression between cancers from the TCGA database and normal samples from the GTEx database. (C, D) ME1 expression level in GENT2 GPL96 and GPL570 . (E) Expression and distribution of ME1 in various organs. The left panel depicts the expression of ME1 in the corresponding tumor tissues, while the right panel represents the expression of ME1 in normal tissues. A darker color indicates a higher expression level of ME1.* p < 0.05, ** p < 0.01, *** p < 0.001.

    Article Snippet: Small interfering RNAs (siRNAs) targeting ME1, along with non-targeting negative controls (NC), were procured from Shanghai GenePharma Co., Ltd. and subsequently transfected into the human ovarian cancer cell lines A2780 and OVCAR3 using Lipofectamine 3000 (Invitrogen), in accordance with the manufacturer’s instructions.

    Techniques: Expressing

    ME1 protein expression levels in pan-cancer. (A-F) The expression of ME1 in both tumor and normal tissues, including the colon, lung, liver, testis, cervix, and thyroid gland, was analyzed using data from the HPA database. (G-N) ME1 protein expression levels in GBM, LUAD, HNSCC, BRCA, COAD, CCRCC, OV and UCEC from the CPTAC database.

    Journal: Frontiers in Immunology

    Article Title: The potential of ME1 in guiding immunotherapeutic strategies for ovarian cancer: insights from pan-cancer research

    doi: 10.3389/fimmu.2025.1571842

    Figure Lengend Snippet: ME1 protein expression levels in pan-cancer. (A-F) The expression of ME1 in both tumor and normal tissues, including the colon, lung, liver, testis, cervix, and thyroid gland, was analyzed using data from the HPA database. (G-N) ME1 protein expression levels in GBM, LUAD, HNSCC, BRCA, COAD, CCRCC, OV and UCEC from the CPTAC database.

    Article Snippet: Small interfering RNAs (siRNAs) targeting ME1, along with non-targeting negative controls (NC), were procured from Shanghai GenePharma Co., Ltd. and subsequently transfected into the human ovarian cancer cell lines A2780 and OVCAR3 using Lipofectamine 3000 (Invitrogen), in accordance with the manufacturer’s instructions.

    Techniques: Expressing

    ME1 mutation, methylation, TMB and MSI analysis. (A) Distribution of ME1 mutations within protein structural domains. (B) Frequency and mutation types of ME1 gene alterations in pan-cancer. (C) Correlation between ME1 expression levels and genetic alterations. (D) DNA methylation levels of the ME1 gene in pan-cancer. (E) Expression levels of the ME1 gene alongside 44 marker genes associated with class III RNA-modified genes [m1A , m5C , m6A ] in each sample. (F) Association between ME1 expression and TMB. (G) The relationship between ME1 and MSI in multiple types of cancer. Significant negative correlation in 5 cancer types (ACC、LUAD、PRAD、THCA、UCS) and significant positive correlation in 2 cancer types (COAD、TGCT). * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001. ns, not significant.

    Journal: Frontiers in Immunology

    Article Title: The potential of ME1 in guiding immunotherapeutic strategies for ovarian cancer: insights from pan-cancer research

    doi: 10.3389/fimmu.2025.1571842

    Figure Lengend Snippet: ME1 mutation, methylation, TMB and MSI analysis. (A) Distribution of ME1 mutations within protein structural domains. (B) Frequency and mutation types of ME1 gene alterations in pan-cancer. (C) Correlation between ME1 expression levels and genetic alterations. (D) DNA methylation levels of the ME1 gene in pan-cancer. (E) Expression levels of the ME1 gene alongside 44 marker genes associated with class III RNA-modified genes [m1A , m5C , m6A ] in each sample. (F) Association between ME1 expression and TMB. (G) The relationship between ME1 and MSI in multiple types of cancer. Significant negative correlation in 5 cancer types (ACC、LUAD、PRAD、THCA、UCS) and significant positive correlation in 2 cancer types (COAD、TGCT). * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001. ns, not significant.

    Article Snippet: Small interfering RNAs (siRNAs) targeting ME1, along with non-targeting negative controls (NC), were procured from Shanghai GenePharma Co., Ltd. and subsequently transfected into the human ovarian cancer cell lines A2780 and OVCAR3 using Lipofectamine 3000 (Invitrogen), in accordance with the manufacturer’s instructions.

    Techniques: Mutagenesis, Methylation, Expressing, DNA Methylation Assay, Marker, Modification

    ME1 evaluation at the single-cell RNA sequencing level. (A) The correlation between the expression of ME1 and the 14 functional states of cancer across pan-cancer was analyzed. (B-D) The identified cell clusters, cell types, and the expression level of ME1 in ovarian cancer tissues based on the OV_GSE115007 dataset. (E-G) The identified cell clusters, cell types, and the expression level of ME1 in breast cancer tissues based on the BRCA_GSE114727_inDrop dataset. (H-J) The identified cell clusters, cell types, and the expression level of ME1 in non-small cell lung cancer tissues based on the NSCLC_GSE127465 dataset.

    Journal: Frontiers in Immunology

    Article Title: The potential of ME1 in guiding immunotherapeutic strategies for ovarian cancer: insights from pan-cancer research

    doi: 10.3389/fimmu.2025.1571842

    Figure Lengend Snippet: ME1 evaluation at the single-cell RNA sequencing level. (A) The correlation between the expression of ME1 and the 14 functional states of cancer across pan-cancer was analyzed. (B-D) The identified cell clusters, cell types, and the expression level of ME1 in ovarian cancer tissues based on the OV_GSE115007 dataset. (E-G) The identified cell clusters, cell types, and the expression level of ME1 in breast cancer tissues based on the BRCA_GSE114727_inDrop dataset. (H-J) The identified cell clusters, cell types, and the expression level of ME1 in non-small cell lung cancer tissues based on the NSCLC_GSE127465 dataset.

    Article Snippet: Small interfering RNAs (siRNAs) targeting ME1, along with non-targeting negative controls (NC), were procured from Shanghai GenePharma Co., Ltd. and subsequently transfected into the human ovarian cancer cell lines A2780 and OVCAR3 using Lipofectamine 3000 (Invitrogen), in accordance with the manufacturer’s instructions.

    Techniques: RNA Sequencing, Expressing, Functional Assay

    Correlation analysis of ME1 and immune regulatory gene, immune checkpoints and tumor stemness score. (A) The correlation of ME1 expression with most immune regulatory gene. (B) The correlation of ME1 and known immune checkpoints across all TCGA cancers. (C) The ME1 tumor stemness score. *P < 0.05.

    Journal: Frontiers in Immunology

    Article Title: The potential of ME1 in guiding immunotherapeutic strategies for ovarian cancer: insights from pan-cancer research

    doi: 10.3389/fimmu.2025.1571842

    Figure Lengend Snippet: Correlation analysis of ME1 and immune regulatory gene, immune checkpoints and tumor stemness score. (A) The correlation of ME1 expression with most immune regulatory gene. (B) The correlation of ME1 and known immune checkpoints across all TCGA cancers. (C) The ME1 tumor stemness score. *P < 0.05.

    Article Snippet: Small interfering RNAs (siRNAs) targeting ME1, along with non-targeting negative controls (NC), were procured from Shanghai GenePharma Co., Ltd. and subsequently transfected into the human ovarian cancer cell lines A2780 and OVCAR3 using Lipofectamine 3000 (Invitrogen), in accordance with the manufacturer’s instructions.

    Techniques: Expressing

    Immune infiltration analysis in pan-cancer. (A-L) Analysis of ME1 expression and immune infiltration score in tumor types. The results indicated that ME1 exhibited a significant positive correlation with immune infiltration in GBM, SARC, KIPAN, PRAD, SKCM, BLCA, LAML, and OV ( p < 0.05). In contrast, in ESCA, STES, and LUSC, ME1 expression was negatively correlated with immune infiltration. (M) Examining the correlations between ME1expression and immune infiltration across all TCGA cancers using TIMER2 algorithms.

    Journal: Frontiers in Immunology

    Article Title: The potential of ME1 in guiding immunotherapeutic strategies for ovarian cancer: insights from pan-cancer research

    doi: 10.3389/fimmu.2025.1571842

    Figure Lengend Snippet: Immune infiltration analysis in pan-cancer. (A-L) Analysis of ME1 expression and immune infiltration score in tumor types. The results indicated that ME1 exhibited a significant positive correlation with immune infiltration in GBM, SARC, KIPAN, PRAD, SKCM, BLCA, LAML, and OV ( p < 0.05). In contrast, in ESCA, STES, and LUSC, ME1 expression was negatively correlated with immune infiltration. (M) Examining the correlations between ME1expression and immune infiltration across all TCGA cancers using TIMER2 algorithms.

    Article Snippet: Small interfering RNAs (siRNAs) targeting ME1, along with non-targeting negative controls (NC), were procured from Shanghai GenePharma Co., Ltd. and subsequently transfected into the human ovarian cancer cell lines A2780 and OVCAR3 using Lipofectamine 3000 (Invitrogen), in accordance with the manufacturer’s instructions.

    Techniques: Expressing

    ME1 Functional enrichment analysis. (A) The protein-protein interaction network of ME1 from STRING. (B) The top 50 genes positively correlated to ME1 in the OV cohort. (C) The top 50 genes negatively correlated to ME1 in OV. (D) KEGG analysis of ME1 co-expression genes in the OV cohort. (E-G) GO analysis (BP, CC, and MF) of ME1 co-expression genes in the OV cohort.

    Journal: Frontiers in Immunology

    Article Title: The potential of ME1 in guiding immunotherapeutic strategies for ovarian cancer: insights from pan-cancer research

    doi: 10.3389/fimmu.2025.1571842

    Figure Lengend Snippet: ME1 Functional enrichment analysis. (A) The protein-protein interaction network of ME1 from STRING. (B) The top 50 genes positively correlated to ME1 in the OV cohort. (C) The top 50 genes negatively correlated to ME1 in OV. (D) KEGG analysis of ME1 co-expression genes in the OV cohort. (E-G) GO analysis (BP, CC, and MF) of ME1 co-expression genes in the OV cohort.

    Article Snippet: Small interfering RNAs (siRNAs) targeting ME1, along with non-targeting negative controls (NC), were procured from Shanghai GenePharma Co., Ltd. and subsequently transfected into the human ovarian cancer cell lines A2780 and OVCAR3 using Lipofectamine 3000 (Invitrogen), in accordance with the manufacturer’s instructions.

    Techniques: Functional Assay, Expressing

    Drug sensitivity analysis and the associations between ME1 expression and immune checkpoint blockade treatment in cancer. (A-J) The box plots of the estimated IC50 displayed the differences of drug sensitivity between the high-risk and low-risk groups in the OV cohort. (K) Overall survival using all anti-CTLA-4 between the high-risk and low-risk groups in the OV cohort. (L) Overall survival using all anti-PD-L1 between the high-risk and low-risk groups in the OV cohort. (M) Overall survival using all Atezolizumab only between the high-risk and low-risk groups in the OV cohort. (N) Overall survival using all Ipilimumab only between the high-risk and low-risk groups in the OV cohort. (O) Overall survival using all Pembrolizumab only between the high-risk and low-risk groups in the OV cohort.

    Journal: Frontiers in Immunology

    Article Title: The potential of ME1 in guiding immunotherapeutic strategies for ovarian cancer: insights from pan-cancer research

    doi: 10.3389/fimmu.2025.1571842

    Figure Lengend Snippet: Drug sensitivity analysis and the associations between ME1 expression and immune checkpoint blockade treatment in cancer. (A-J) The box plots of the estimated IC50 displayed the differences of drug sensitivity between the high-risk and low-risk groups in the OV cohort. (K) Overall survival using all anti-CTLA-4 between the high-risk and low-risk groups in the OV cohort. (L) Overall survival using all anti-PD-L1 between the high-risk and low-risk groups in the OV cohort. (M) Overall survival using all Atezolizumab only between the high-risk and low-risk groups in the OV cohort. (N) Overall survival using all Ipilimumab only between the high-risk and low-risk groups in the OV cohort. (O) Overall survival using all Pembrolizumab only between the high-risk and low-risk groups in the OV cohort.

    Article Snippet: Small interfering RNAs (siRNAs) targeting ME1, along with non-targeting negative controls (NC), were procured from Shanghai GenePharma Co., Ltd. and subsequently transfected into the human ovarian cancer cell lines A2780 and OVCAR3 using Lipofectamine 3000 (Invitrogen), in accordance with the manufacturer’s instructions.

    Techniques: Expressing

    ME1 knockdown suppressed the proliferation and migration in OV cell lines. (A) ME1 basal expression in normal ovarian cells (IOSE80) and in human ovarian cancer cell lines (A2780, and OVCAR3). (B, C) WB and qRT-PCR results confirmed the effective knockdown of the ME1 gene mediated by siRNA in the A2780 and OVCAR3 cell lines, respectively. (D) CCK-8 assay results indicated that the knockdown of the ME1 gene inhibited the proliferative capacity of both A2780 and OVCAR3 cell lines. (E) Clone formation assay further corroborated that ME1 knockdown reduced the proliferative ability of A2780 and OVCAR3 cells. (F) Cell scratch assays revealed a significant decrease in the migration of A2780 and OVCAR3 cells following ME1 knockdown. (G) Transwell assays demonstrated that silencing ME1 markedly impaired the migratory capability of A2780 and OVCAR3 cells.* p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001.

    Journal: Frontiers in Immunology

    Article Title: The potential of ME1 in guiding immunotherapeutic strategies for ovarian cancer: insights from pan-cancer research

    doi: 10.3389/fimmu.2025.1571842

    Figure Lengend Snippet: ME1 knockdown suppressed the proliferation and migration in OV cell lines. (A) ME1 basal expression in normal ovarian cells (IOSE80) and in human ovarian cancer cell lines (A2780, and OVCAR3). (B, C) WB and qRT-PCR results confirmed the effective knockdown of the ME1 gene mediated by siRNA in the A2780 and OVCAR3 cell lines, respectively. (D) CCK-8 assay results indicated that the knockdown of the ME1 gene inhibited the proliferative capacity of both A2780 and OVCAR3 cell lines. (E) Clone formation assay further corroborated that ME1 knockdown reduced the proliferative ability of A2780 and OVCAR3 cells. (F) Cell scratch assays revealed a significant decrease in the migration of A2780 and OVCAR3 cells following ME1 knockdown. (G) Transwell assays demonstrated that silencing ME1 markedly impaired the migratory capability of A2780 and OVCAR3 cells.* p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001.

    Article Snippet: Small interfering RNAs (siRNAs) targeting ME1, along with non-targeting negative controls (NC), were procured from Shanghai GenePharma Co., Ltd. and subsequently transfected into the human ovarian cancer cell lines A2780 and OVCAR3 using Lipofectamine 3000 (Invitrogen), in accordance with the manufacturer’s instructions.

    Techniques: Knockdown, Migration, Expressing, Quantitative RT-PCR, CCK-8 Assay, Tube Formation Assay

    ME1 overexpression promoted the proliferation and migration in OV cell lines. (A) WB analysis of ME1 protein expression was conducted in vector-control cells (vector) and ME1-overexpressing cells (ME1_OE). (B, C) The overexpression of ME1 significantly enhanced proliferative activity, as demonstrated by the CCK-8 assay and colony formation assay. (D, E) Both the cell scratch assay and transwell migration assay indicated that ME1 overexpression resulted in an increased number of migrating cells. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

    Journal: Frontiers in Immunology

    Article Title: The potential of ME1 in guiding immunotherapeutic strategies for ovarian cancer: insights from pan-cancer research

    doi: 10.3389/fimmu.2025.1571842

    Figure Lengend Snippet: ME1 overexpression promoted the proliferation and migration in OV cell lines. (A) WB analysis of ME1 protein expression was conducted in vector-control cells (vector) and ME1-overexpressing cells (ME1_OE). (B, C) The overexpression of ME1 significantly enhanced proliferative activity, as demonstrated by the CCK-8 assay and colony formation assay. (D, E) Both the cell scratch assay and transwell migration assay indicated that ME1 overexpression resulted in an increased number of migrating cells. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

    Article Snippet: Small interfering RNAs (siRNAs) targeting ME1, along with non-targeting negative controls (NC), were procured from Shanghai GenePharma Co., Ltd. and subsequently transfected into the human ovarian cancer cell lines A2780 and OVCAR3 using Lipofectamine 3000 (Invitrogen), in accordance with the manufacturer’s instructions.

    Techniques: Over Expression, Migration, Expressing, Plasmid Preparation, Control, Activity Assay, CCK-8 Assay, Colony Assay, Wound Healing Assay, Transwell Migration Assay

    MICAL1 expression and diagnostic value in pan-cancer. (a) MICAL1 mRNA expression ranked from high to low across multiple cancer types; (b) MICAL1 mRNA expression in tumor vs normal tissues for selected cancer types; (c) MICAL1 mRNA expression by cancer stage for selected cancer types; (d) ROC curve analysis of MICAL1 expression for distinguishing tumor from normal tissues; (e) MICAL1 protein expression in tumor vs normal tissues for selected cancer types. *** p < .001, ** p < .01, * p < .05.

    Journal: Cell Adhesion & Migration

    Article Title: Elucidating the role of MICAL1 in pan-cancer using integrated bioinformatics and experimental approaches

    doi: 10.1080/19336918.2024.2335682

    Figure Lengend Snippet: MICAL1 expression and diagnostic value in pan-cancer. (a) MICAL1 mRNA expression ranked from high to low across multiple cancer types; (b) MICAL1 mRNA expression in tumor vs normal tissues for selected cancer types; (c) MICAL1 mRNA expression by cancer stage for selected cancer types; (d) ROC curve analysis of MICAL1 expression for distinguishing tumor from normal tissues; (e) MICAL1 protein expression in tumor vs normal tissues for selected cancer types. *** p < .001, ** p < .01, * p < .05.

    Article Snippet: Small interfering RNAs (siRNAs) targeting MICAL1 and non-targeting negative controls (NC) were obtained from Shanghai GenePharma Co., Ltd (GenePharma) and transfected into Clear Cell Renal Cell Carcinoma (ccRCC) cells using Lipofectamine 3000 (Invitrogen) following the manufacturer’s instructions.

    Techniques: Expressing, Diagnostic Assay

    Association between MICAL1 expression and survival outcomes. (a) Overall survival; (b) disease-specific survival; (c) disease-free survival; (d) progression-free survival.

    Journal: Cell Adhesion & Migration

    Article Title: Elucidating the role of MICAL1 in pan-cancer using integrated bioinformatics and experimental approaches

    doi: 10.1080/19336918.2024.2335682

    Figure Lengend Snippet: Association between MICAL1 expression and survival outcomes. (a) Overall survival; (b) disease-specific survival; (c) disease-free survival; (d) progression-free survival.

    Article Snippet: Small interfering RNAs (siRNAs) targeting MICAL1 and non-targeting negative controls (NC) were obtained from Shanghai GenePharma Co., Ltd (GenePharma) and transfected into Clear Cell Renal Cell Carcinoma (ccRCC) cells using Lipofectamine 3000 (Invitrogen) following the manufacturer’s instructions.

    Techniques: Expressing

    Kaplan-Meier curves showing overall survival of cancer patients stratified by MICAL1 expression levels. In LAML, ACC, KIRC, MESO, and UVM patients, high MICAL1 expression was associated with significantly worse overall survival compared to low expression. In LUAD, BRCA, PAAD and HNSC patients, low MICAL1 expression was associated with significantly worse overall survival compared to high expression.

    Journal: Cell Adhesion & Migration

    Article Title: Elucidating the role of MICAL1 in pan-cancer using integrated bioinformatics and experimental approaches

    doi: 10.1080/19336918.2024.2335682

    Figure Lengend Snippet: Kaplan-Meier curves showing overall survival of cancer patients stratified by MICAL1 expression levels. In LAML, ACC, KIRC, MESO, and UVM patients, high MICAL1 expression was associated with significantly worse overall survival compared to low expression. In LUAD, BRCA, PAAD and HNSC patients, low MICAL1 expression was associated with significantly worse overall survival compared to high expression.

    Article Snippet: Small interfering RNAs (siRNAs) targeting MICAL1 and non-targeting negative controls (NC) were obtained from Shanghai GenePharma Co., Ltd (GenePharma) and transfected into Clear Cell Renal Cell Carcinoma (ccRCC) cells using Lipofectamine 3000 (Invitrogen) following the manufacturer’s instructions.

    Techniques: Expressing

    MICAL1 expression is associated with survival outcomes across multiple cancer types. (a-f) Kaplan-Meier curves of progression free survival based on MICAL1 expression levels in ACC, MESO, COAD, LUSC, READ and PAAD;(g-j) Kaplan-Meier curves of disease specific survival based on MICAL1 expression levels in ACC, KIRC, MESO, PAAD; (h) Kaplan-Meier curves of disease-free survival based on MICAL1 expression levels in COAD.

    Journal: Cell Adhesion & Migration

    Article Title: Elucidating the role of MICAL1 in pan-cancer using integrated bioinformatics and experimental approaches

    doi: 10.1080/19336918.2024.2335682

    Figure Lengend Snippet: MICAL1 expression is associated with survival outcomes across multiple cancer types. (a-f) Kaplan-Meier curves of progression free survival based on MICAL1 expression levels in ACC, MESO, COAD, LUSC, READ and PAAD;(g-j) Kaplan-Meier curves of disease specific survival based on MICAL1 expression levels in ACC, KIRC, MESO, PAAD; (h) Kaplan-Meier curves of disease-free survival based on MICAL1 expression levels in COAD.

    Article Snippet: Small interfering RNAs (siRNAs) targeting MICAL1 and non-targeting negative controls (NC) were obtained from Shanghai GenePharma Co., Ltd (GenePharma) and transfected into Clear Cell Renal Cell Carcinoma (ccRCC) cells using Lipofectamine 3000 (Invitrogen) following the manufacturer’s instructions.

    Techniques: Expressing

    MICAL1 expression is associated with genomic and transcriptomic instability across cancer types. (a) Association between MICAL1 expression and microsatellite instability; (b) association between MICAL1 expression and tumor mutation burden; (c) association between MICAL1 expression and DNA stability scores; (d) association between MICAL1 expression and RNA stability scores; (e) correlations between MICAL1 expression and mismatch repair genes. *** p < .001, ** p < .01, * p < .05.

    Journal: Cell Adhesion & Migration

    Article Title: Elucidating the role of MICAL1 in pan-cancer using integrated bioinformatics and experimental approaches

    doi: 10.1080/19336918.2024.2335682

    Figure Lengend Snippet: MICAL1 expression is associated with genomic and transcriptomic instability across cancer types. (a) Association between MICAL1 expression and microsatellite instability; (b) association between MICAL1 expression and tumor mutation burden; (c) association between MICAL1 expression and DNA stability scores; (d) association between MICAL1 expression and RNA stability scores; (e) correlations between MICAL1 expression and mismatch repair genes. *** p < .001, ** p < .01, * p < .05.

    Article Snippet: Small interfering RNAs (siRNAs) targeting MICAL1 and non-targeting negative controls (NC) were obtained from Shanghai GenePharma Co., Ltd (GenePharma) and transfected into Clear Cell Renal Cell Carcinoma (ccRCC) cells using Lipofectamine 3000 (Invitrogen) following the manufacturer’s instructions.

    Techniques: Expressing, Mutagenesis

    Functional analysis of MICAL1 in various cancers (a) the protein – protein interaction network of MICAL1 from STRING; (b) the gene–gene interaction network of MICAL1 from GeneMANIA; (c) biological process (BP) functional analysis of MICAL1 and its functional partners; (d) cellular components (CC) functional analysis of MICAL1 and its functional partners; (e) molecular function (MF) functional analysis of MICAL1 and its functional partners; (f) Kyoto Encyclopedia of Genes and genomes (KEGG) pathway analysis of MICAL1 and its functional partners; (g) gene Set Enrichment analysis of MICAL1 in pan-caner.

    Journal: Cell Adhesion & Migration

    Article Title: Elucidating the role of MICAL1 in pan-cancer using integrated bioinformatics and experimental approaches

    doi: 10.1080/19336918.2024.2335682

    Figure Lengend Snippet: Functional analysis of MICAL1 in various cancers (a) the protein – protein interaction network of MICAL1 from STRING; (b) the gene–gene interaction network of MICAL1 from GeneMANIA; (c) biological process (BP) functional analysis of MICAL1 and its functional partners; (d) cellular components (CC) functional analysis of MICAL1 and its functional partners; (e) molecular function (MF) functional analysis of MICAL1 and its functional partners; (f) Kyoto Encyclopedia of Genes and genomes (KEGG) pathway analysis of MICAL1 and its functional partners; (g) gene Set Enrichment analysis of MICAL1 in pan-caner.

    Article Snippet: Small interfering RNAs (siRNAs) targeting MICAL1 and non-targeting negative controls (NC) were obtained from Shanghai GenePharma Co., Ltd (GenePharma) and transfected into Clear Cell Renal Cell Carcinoma (ccRCC) cells using Lipofectamine 3000 (Invitrogen) following the manufacturer’s instructions.

    Techniques: Functional Assay

    Correlation of MICAL1 expression with immune infiltration and immunosuppression across different cancer types. (a-c) correlation between MICAL1 expression and stromal score, immune score, and ESTIMATE score levels based on ESTIMATE algorithm; (d) correlation between MICAL1 expression and immune cell fractions estimated by CIBERSORT algorithm; (e) correlation between MICAL1 expression and expression of immunosuppressive molecules including LAG3, CTLA4, HAVCR2, PDCD1, TIGIT, and CD274. *** p < .001, ** p < .01, * p < .05.

    Journal: Cell Adhesion & Migration

    Article Title: Elucidating the role of MICAL1 in pan-cancer using integrated bioinformatics and experimental approaches

    doi: 10.1080/19336918.2024.2335682

    Figure Lengend Snippet: Correlation of MICAL1 expression with immune infiltration and immunosuppression across different cancer types. (a-c) correlation between MICAL1 expression and stromal score, immune score, and ESTIMATE score levels based on ESTIMATE algorithm; (d) correlation between MICAL1 expression and immune cell fractions estimated by CIBERSORT algorithm; (e) correlation between MICAL1 expression and expression of immunosuppressive molecules including LAG3, CTLA4, HAVCR2, PDCD1, TIGIT, and CD274. *** p < .001, ** p < .01, * p < .05.

    Article Snippet: Small interfering RNAs (siRNAs) targeting MICAL1 and non-targeting negative controls (NC) were obtained from Shanghai GenePharma Co., Ltd (GenePharma) and transfected into Clear Cell Renal Cell Carcinoma (ccRCC) cells using Lipofectamine 3000 (Invitrogen) following the manufacturer’s instructions.

    Techniques: Expressing

    Correlation between MICAL1 expression and drug response.

    Journal: Cell Adhesion & Migration

    Article Title: Elucidating the role of MICAL1 in pan-cancer using integrated bioinformatics and experimental approaches

    doi: 10.1080/19336918.2024.2335682

    Figure Lengend Snippet: Correlation between MICAL1 expression and drug response.

    Article Snippet: Small interfering RNAs (siRNAs) targeting MICAL1 and non-targeting negative controls (NC) were obtained from Shanghai GenePharma Co., Ltd (GenePharma) and transfected into Clear Cell Renal Cell Carcinoma (ccRCC) cells using Lipofectamine 3000 (Invitrogen) following the manufacturer’s instructions.

    Techniques: Expressing

    MICAL1 knockdown suppressed the proliferation and migration in clear cell renal cell carcinoma cell lines. (a) MICAL1 expression increases in clear cell renal cell carcinoma cell lines; (b-d) qRT-PCR results verified the knockdown effect of MICAL gene mediated by siRnas in ACHN, CAKI-1 and 786-O cell lines, respectively; (e-g) CCK-8 assay results showed that knockdown of MICAL1 gene inhibited the proliferative ability of ACHN, CAKI-1 and 786-O cell lines;(G-I) the migration number of ACHN, CAKI-1 and 786-O cells significantly decreased after MICAL1 knockdown. *** p < .001, ** p < .01.

    Journal: Cell Adhesion & Migration

    Article Title: Elucidating the role of MICAL1 in pan-cancer using integrated bioinformatics and experimental approaches

    doi: 10.1080/19336918.2024.2335682

    Figure Lengend Snippet: MICAL1 knockdown suppressed the proliferation and migration in clear cell renal cell carcinoma cell lines. (a) MICAL1 expression increases in clear cell renal cell carcinoma cell lines; (b-d) qRT-PCR results verified the knockdown effect of MICAL gene mediated by siRnas in ACHN, CAKI-1 and 786-O cell lines, respectively; (e-g) CCK-8 assay results showed that knockdown of MICAL1 gene inhibited the proliferative ability of ACHN, CAKI-1 and 786-O cell lines;(G-I) the migration number of ACHN, CAKI-1 and 786-O cells significantly decreased after MICAL1 knockdown. *** p < .001, ** p < .01.

    Article Snippet: Small interfering RNAs (siRNAs) targeting MICAL1 and non-targeting negative controls (NC) were obtained from Shanghai GenePharma Co., Ltd (GenePharma) and transfected into Clear Cell Renal Cell Carcinoma (ccRCC) cells using Lipofectamine 3000 (Invitrogen) following the manufacturer’s instructions.

    Techniques: Knockdown, Migration, Expressing, Quantitative RT-PCR, CCK-8 Assay

    MICAL1 overexpression promoted the proliferation and migration in clear cell renal cell carcinoma in vitro. (A) qRT-PCR of MICAL1 mRNA expression in vector-control cells (vector) and MICAL1-overexpressing cells (MICAL1); (B) MICAL1 overexpression significantly enhanced the proliferative activity as evidenced using CCK-8 assay. (C-D) transwell migration assay revealed that MICAL1 overexpression increased the cell numbers of migration. *** p < .001, ** p < .01.

    Journal: Cell Adhesion & Migration

    Article Title: Elucidating the role of MICAL1 in pan-cancer using integrated bioinformatics and experimental approaches

    doi: 10.1080/19336918.2024.2335682

    Figure Lengend Snippet: MICAL1 overexpression promoted the proliferation and migration in clear cell renal cell carcinoma in vitro. (A) qRT-PCR of MICAL1 mRNA expression in vector-control cells (vector) and MICAL1-overexpressing cells (MICAL1); (B) MICAL1 overexpression significantly enhanced the proliferative activity as evidenced using CCK-8 assay. (C-D) transwell migration assay revealed that MICAL1 overexpression increased the cell numbers of migration. *** p < .001, ** p < .01.

    Article Snippet: Small interfering RNAs (siRNAs) targeting MICAL1 and non-targeting negative controls (NC) were obtained from Shanghai GenePharma Co., Ltd (GenePharma) and transfected into Clear Cell Renal Cell Carcinoma (ccRCC) cells using Lipofectamine 3000 (Invitrogen) following the manufacturer’s instructions.

    Techniques: Over Expression, Migration, In Vitro, Quantitative RT-PCR, Expressing, Plasmid Preparation, Control, Activity Assay, CCK-8 Assay, Transwell Migration Assay

    Expression of Testis-specific transcript, Y-linked 14 (TTTY14). (A) GEPIA was used to analyze the expression of TTTY14 in various tumors. TTTY14 is highly expressed in GBM, PRAD and TGCT. The normalization method is Transcripts Per Million (TPM). The scale of y-axis is log2(TPM+1). (B) The expression of TTTY14 in normal testis samples and testicular tumor samples was analyzed using the GSE3218 dataset in the GEO database. (C) The expression of TTTY14 in non-seminoma and seminoma was analyzed by GEPIA. (D) The TGCT cohort data was downloaded from the UCSC XENA database to analyze the expression of TTTY14 in intratubular germ cell tumors. *P < 0.05, **P < 0.01.

    Journal: Heliyon

    Article Title: Long non-coding RNA TTTY14 promotes cell proliferation and functions as a prognostic biomarker in testicular germ cell tumor

    doi: 10.1016/j.heliyon.2023.e16082

    Figure Lengend Snippet: Expression of Testis-specific transcript, Y-linked 14 (TTTY14). (A) GEPIA was used to analyze the expression of TTTY14 in various tumors. TTTY14 is highly expressed in GBM, PRAD and TGCT. The normalization method is Transcripts Per Million (TPM). The scale of y-axis is log2(TPM+1). (B) The expression of TTTY14 in normal testis samples and testicular tumor samples was analyzed using the GSE3218 dataset in the GEO database. (C) The expression of TTTY14 in non-seminoma and seminoma was analyzed by GEPIA. (D) The TGCT cohort data was downloaded from the UCSC XENA database to analyze the expression of TTTY14 in intratubular germ cell tumors. *P < 0.05, **P < 0.01.

    Article Snippet: The TTTY14 siRNA sequences and non-target negative control (NC) was synthesized by Ribobio (Guangzhou, China).

    Techniques: Expressing

    The association between TTTY14 expression, methylation, and copy number in TCGA TGCT cohort. The UCSC XENA database was used to download the methylation data, expression data, and prognosis data of TTTY14 from the TCGA TGCT cohort. (A–B) The copy number was significantly positively correlated with TTTY14 expression. The copy number column was sorted from smallest to largest values. The redder the color, the larger the value; the bluer the value, smaller the value. (C) Correlation between TTTY14 copy number and overall survival of TGCT cohort from TCGA. Patients with high TTTY14 copy number had lower survival probability. (D) The CpG sites of TTTY14 were showed. (E–F) TTTY14 methylation level was significantly negatively correlated with its expression. The DNA methylation column was sorted from smallest to largest values. The redder the color, the larger the value; the bluer the value, smaller the value. CNV, copy number various. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

    Journal: Heliyon

    Article Title: Long non-coding RNA TTTY14 promotes cell proliferation and functions as a prognostic biomarker in testicular germ cell tumor

    doi: 10.1016/j.heliyon.2023.e16082

    Figure Lengend Snippet: The association between TTTY14 expression, methylation, and copy number in TCGA TGCT cohort. The UCSC XENA database was used to download the methylation data, expression data, and prognosis data of TTTY14 from the TCGA TGCT cohort. (A–B) The copy number was significantly positively correlated with TTTY14 expression. The copy number column was sorted from smallest to largest values. The redder the color, the larger the value; the bluer the value, smaller the value. (C) Correlation between TTTY14 copy number and overall survival of TGCT cohort from TCGA. Patients with high TTTY14 copy number had lower survival probability. (D) The CpG sites of TTTY14 were showed. (E–F) TTTY14 methylation level was significantly negatively correlated with its expression. The DNA methylation column was sorted from smallest to largest values. The redder the color, the larger the value; the bluer the value, smaller the value. CNV, copy number various. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

    Article Snippet: The TTTY14 siRNA sequences and non-target negative control (NC) was synthesized by Ribobio (Guangzhou, China).

    Techniques: Expressing, Methylation, DNA Methylation Assay

    Relationship between TTTY14 and survival prognosis of TGCT patients. Based on TCGA TGCT data, the Kaplan-Meier Plotter online tool was used to analyze relationship between TTTY14 expression and two-year survival in TGCT patients. (A) The relationship between TTTY14 expression and two-year survival in all TGCT patients was analyzed. (B) The relationship between TTTY14 expression and two-year survival in TGCT patients with high tumor mutational burden (TMB) was analyzed. (C) The relationship between TTTY14 expression and two-year survival in TGCT patients with low TMB was analyzed. (D) The relationship between TTTY14 expression and two-year survival in CD8 + T cell-enriched TGCT patients was analyzed. (E) The relationship between TTTY14 expression and two-year survival in patients with TGCT CD8 + T cell-deserted was analyzed.

    Journal: Heliyon

    Article Title: Long non-coding RNA TTTY14 promotes cell proliferation and functions as a prognostic biomarker in testicular germ cell tumor

    doi: 10.1016/j.heliyon.2023.e16082

    Figure Lengend Snippet: Relationship between TTTY14 and survival prognosis of TGCT patients. Based on TCGA TGCT data, the Kaplan-Meier Plotter online tool was used to analyze relationship between TTTY14 expression and two-year survival in TGCT patients. (A) The relationship between TTTY14 expression and two-year survival in all TGCT patients was analyzed. (B) The relationship between TTTY14 expression and two-year survival in TGCT patients with high tumor mutational burden (TMB) was analyzed. (C) The relationship between TTTY14 expression and two-year survival in TGCT patients with low TMB was analyzed. (D) The relationship between TTTY14 expression and two-year survival in CD8 + T cell-enriched TGCT patients was analyzed. (E) The relationship between TTTY14 expression and two-year survival in patients with TGCT CD8 + T cell-deserted was analyzed.

    Article Snippet: The TTTY14 siRNA sequences and non-target negative control (NC) was synthesized by Ribobio (Guangzhou, China).

    Techniques: Expressing

    Knockdown of TTTY14 inhibits NCCIT cell proliferation. (A) NCCIT cells were transfected with TTTY14 siRNA, and the expression of TTTY14 was detected by qPCR. (B) Edu staining was used to measure the proliferation of NCCIT cells transfected with TTTY14 siRNA. (C) CCK8 assay for cell viability of NCCIT cells transfected with TTTY14 siRNA. (D) Colony formation assay was used to detect the cell cloning ability of NCCIT cells transfected with TTTY14 siRNA. *P < 0.05, **P < 0.01, ***P < 0.001.

    Journal: Heliyon

    Article Title: Long non-coding RNA TTTY14 promotes cell proliferation and functions as a prognostic biomarker in testicular germ cell tumor

    doi: 10.1016/j.heliyon.2023.e16082

    Figure Lengend Snippet: Knockdown of TTTY14 inhibits NCCIT cell proliferation. (A) NCCIT cells were transfected with TTTY14 siRNA, and the expression of TTTY14 was detected by qPCR. (B) Edu staining was used to measure the proliferation of NCCIT cells transfected with TTTY14 siRNA. (C) CCK8 assay for cell viability of NCCIT cells transfected with TTTY14 siRNA. (D) Colony formation assay was used to detect the cell cloning ability of NCCIT cells transfected with TTTY14 siRNA. *P < 0.05, **P < 0.01, ***P < 0.001.

    Article Snippet: The TTTY14 siRNA sequences and non-target negative control (NC) was synthesized by Ribobio (Guangzhou, China).

    Techniques: Knockdown, Transfection, Expressing, Staining, CCK-8 Assay, Colony Assay, Cloning

    The correlation between TTTY14 and antitumor drug sensitivity. GSCA online tool was used to analyze the correlation between TTTY14 expression and the sensitivity of Genomics of Drug Sensitivity in Cancer (GDSC) drugs (top 30) in TGCT (A), and the correlation between TTTY14 expression and the sensitivity of cancer therapeutics response portal (CTRP) drugs (top 30) in TGCT (B). (C) Based on anti -PD1 cohort data, the Kaplan-Meier Plotter online tool was used to analyze the correlation between TTTY14 expression and the immune checkpoint inhibitors. Relationship between overall survival and progression-free survival in this cohort of patients was shown. High expression of TTTY14 is a predictive marker for poor outcome of anti -PD1immunotherapy in TGCT patients.

    Journal: Heliyon

    Article Title: Long non-coding RNA TTTY14 promotes cell proliferation and functions as a prognostic biomarker in testicular germ cell tumor

    doi: 10.1016/j.heliyon.2023.e16082

    Figure Lengend Snippet: The correlation between TTTY14 and antitumor drug sensitivity. GSCA online tool was used to analyze the correlation between TTTY14 expression and the sensitivity of Genomics of Drug Sensitivity in Cancer (GDSC) drugs (top 30) in TGCT (A), and the correlation between TTTY14 expression and the sensitivity of cancer therapeutics response portal (CTRP) drugs (top 30) in TGCT (B). (C) Based on anti -PD1 cohort data, the Kaplan-Meier Plotter online tool was used to analyze the correlation between TTTY14 expression and the immune checkpoint inhibitors. Relationship between overall survival and progression-free survival in this cohort of patients was shown. High expression of TTTY14 is a predictive marker for poor outcome of anti -PD1immunotherapy in TGCT patients.

    Article Snippet: The TTTY14 siRNA sequences and non-target negative control (NC) was synthesized by Ribobio (Guangzhou, China).

    Techniques: Expressing, Marker

    The TTTY14-associated genes, proteins, and pathways. Based on the TCGA TGCT expression profile data, LinkedOmics was used to analyze the positively associated genes and negatively associated genes of TTTY14 (A), and the associated proteins of TTTY14 (B). (C) GSEA enrichment was performed to analyze the associated pathway of TTTY14.

    Journal: Heliyon

    Article Title: Long non-coding RNA TTTY14 promotes cell proliferation and functions as a prognostic biomarker in testicular germ cell tumor

    doi: 10.1016/j.heliyon.2023.e16082

    Figure Lengend Snippet: The TTTY14-associated genes, proteins, and pathways. Based on the TCGA TGCT expression profile data, LinkedOmics was used to analyze the positively associated genes and negatively associated genes of TTTY14 (A), and the associated proteins of TTTY14 (B). (C) GSEA enrichment was performed to analyze the associated pathway of TTTY14.

    Article Snippet: The TTTY14 siRNA sequences and non-target negative control (NC) was synthesized by Ribobio (Guangzhou, China).

    Techniques: Expressing

    Relationship between TTTY14 expression, immune cells and immune checkpoint molecules. Based on the TCGA TGCT cohort data, the ASSISTANT for Clinical Bioinformatics tool was used to analyze the abundance of various immune cells in TGCT samples (A), the correlation between TTTY14 expression and immune dysregulation score (B), and the correlation between TTTY14 and the abundance of various immune cells (C). (D) The correlation between TTTY14 and three immune checkpoint molecules CD274, CTLA4 and HAVCR2 was analyzed using the GEPIA database.

    Journal: Heliyon

    Article Title: Long non-coding RNA TTTY14 promotes cell proliferation and functions as a prognostic biomarker in testicular germ cell tumor

    doi: 10.1016/j.heliyon.2023.e16082

    Figure Lengend Snippet: Relationship between TTTY14 expression, immune cells and immune checkpoint molecules. Based on the TCGA TGCT cohort data, the ASSISTANT for Clinical Bioinformatics tool was used to analyze the abundance of various immune cells in TGCT samples (A), the correlation between TTTY14 expression and immune dysregulation score (B), and the correlation between TTTY14 and the abundance of various immune cells (C). (D) The correlation between TTTY14 and three immune checkpoint molecules CD274, CTLA4 and HAVCR2 was analyzed using the GEPIA database.

    Article Snippet: The TTTY14 siRNA sequences and non-target negative control (NC) was synthesized by Ribobio (Guangzhou, China).

    Techniques: Expressing